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Learning Tabu Search for Combinatorial Optimization

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Operations Research and Enterprise Systems (ICORES 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 509))

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Abstract

In this paper, a new type of local search algorithm is proposed, called Learning Tabu Search and denoted \(\textit{LTS}\). It is assumed that any solution of the considered problem can be represented with a list of characteristics. \(\textit{LTS}\) involves a learning process relying on a trail system. The trail system is based on the idea that if some combinations of characteristics often belong to good solutions during the search process, such combinations of characteristics should be favored when generating new solutions. It will be showed that \(\textit{LTS}\) obtained promising results on a refueling problem in a railway network.

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Authors and Affiliations

  1. Geneva School of Economics and Management, GSEM, University of Geneva, Blvd du Pont-d’Arve 40, 1211, Geneva, Switzerland

    Nicolas Zufferey

  2. Geneva School of Business Administration, Rte de Drize 7, 1227, Carouge, Switzerland

    David Schindl

Authors
  1. Nicolas Zufferey
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  2. David Schindl
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Corresponding author

Correspondence to Nicolas Zufferey .

Editor information

Editors and Affiliations

  1. IMA, LISA, Angers, France

    Eric Pinson

  2. Polytechnic Institute of Setúbal, Setúbal, Portugal

    Fernando Valente

  3. Complutense University, Madrid, Spain

    Begoña Vitoriano

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Zufferey, N., Schindl, D. (2015). Learning Tabu Search for Combinatorial Optimization. In: Pinson, E., Valente, F., Vitoriano, B. (eds) Operations Research and Enterprise Systems. ICORES 2014. Communications in Computer and Information Science, vol 509. Springer, Cham. https://doi.org/10.1007/978-3-319-17509-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-17509-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17508-9

  • Online ISBN: 978-3-319-17509-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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